- Open account settings.
- Scroll down to API and click Create New API Token.
- Open up
kaggle.jsonand use the username and key.
This notebook is a template with each step that you need to complete for the project.
Please fill in your code where there are explicit ? markers in the notebook. You are welcome to add more cells and code as you see fit.
Once you have completed all the code implementations, please export your notebook as a HTML file so the reviews can view your code. Make sure you have all outputs correctly outputted.
File-> Export Notebook As... -> Export Notebook as HTML
There is a writeup to complete as well after all code implememtation is done. Please answer all questions and attach the necessary tables and charts. You can complete the writeup in either markdown or PDF.
Completing the code template and writeup template will cover all of the rubric points for this project.
The rubric contains "Stand Out Suggestions" for enhancing the project beyond the minimum requirements. The stand out suggestions are optional. If you decide to pursue the "stand out suggestions", you can include the code in this notebook and also discuss the results in the writeup file.
Below is example of steps to get the API username and key. Each student will have their own username and key.
kaggle.json and use the username and key.
ml.t3.medium instance (2 vCPU + 4 GiB)Python 3 (MXNet 1.8 Python 3.7 CPU Optimized)!pip install -U pip
!pip install -U setuptools wheel
!pip install -U "mxnet<2.0.0" bokeh==2.0.1
!pip install autogluon --no-cache-dir
# Without --no-cache-dir, smaller aws instances may have trouble installing
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WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
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WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
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Building wheels for collected packages: bokeh
Building wheel for bokeh (setup.py) ... done
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WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
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Building wheels for collected packages: fairscale, antlr4-python3-runtime, seqeval, future
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Successfully built fairscale antlr4-python3-runtime seqeval future
Installing collected packages: typish, tokenizers, text-unidecode, tensorboard-plugin-wit, sortedcontainers, sentencepiece, py4j, msgpack, heapdict, distlib, cymem, antlr4-python3-runtime, zict, yacs, xxhash, wrapt, typing-extensions, tqdm, toolz, tensorboard-data-server, tblib, spacy-loggers, spacy-legacy, smart-open, regex, pyrsistent, pyDeprecate, pyasn1-modules, Pillow, ordered-set, omegaconf, oauthlib, numpy, murmurhash, multidict, mdurl, locket, langcodes, importlib-resources, grpcio, future, frozenlist, filelock, fastprogress, defusedxml, charset-normalizer, cachetools, autocfg, asynctest, absl-py, yarl, wasabi, torch, tifffile, tensorboardX, scipy, responses, requests-oauthlib, PyWavelets, pydantic, pyarrow, preshed, platformdirs, patsy, partd, opencv-python-headless, nptyping, markdown-it-py, importlib-metadata, google-auth, fastcore, deprecated, catalogue, blis, async-timeout, aiosignal, xgboost, virtualenv, torchvision, torchtext, torchmetrics, statsmodels, srsly, scikit-image, rich, nlpaug, markdown, jsonschema, hyperopt, huggingface-hub, google-auth-oauthlib, gluonts, fastdownload, fairscale, dask, click, aiohttp, accelerate, typer, transformers, timm, tensorboard, sktime, seqeval, ray, qudida, pytorch-metric-learning, pmdarima, nltk, model-index, lightgbm, gluoncv, distributed, confection, catboost, thinc, tbats, pytorch-lightning, pathy, openmim, datasets, autogluon.common, albumentations, spacy, evaluate, autogluon.features, autogluon.core, fastai, autogluon.tabular, autogluon.multimodal, autogluon.vision, autogluon.timeseries, autogluon.text, autogluon
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WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
# create the .kaggle directory and an empty kaggle.json file
!mkdir -p /root/.kaggle
!touch /root/.kaggle/kaggle.json
!chmod 600 /root/.kaggle/kaggle.json
# Fill in your user name and key from creating the kaggle account and API token file
import json
kaggle_username = "kr1shn6"
kaggle_key = "30facf08f77e16221c2a269a0242866f"
# Save API token the kaggle.json file
with open("/root/.kaggle/kaggle.json", "w") as f:
f.write(json.dumps({"username": kaggle_username, "key": kaggle_key}))
!pip install kaggle
Collecting kaggle
Downloading kaggle-1.5.13.tar.gz (63 kB)
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Building wheels for collected packages: kaggle
Building wheel for kaggle (setup.py) ... done
Created wheel for kaggle: filename=kaggle-1.5.13-py3-none-any.whl size=77717 sha256=521de080f786a2bb5f1a4f4fc489edd98e85203907e29d8f9935946e57a7ccb9
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Successfully built kaggle
Installing collected packages: python-slugify, kaggle
Successfully installed kaggle-1.5.13 python-slugify-8.0.1
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
# Download the dataset, it will be in a .zip file so you'll need to unzip it as well.
!kaggle competitions download -c bike-sharing-demand
# If you already downloaded it you can use the -o command to overwrite the file
!unzip -o bike-sharing-demand.zip
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import pandas as pd
from autogluon.tabular import TabularPredictor
# Run this cell to import or install the Data Wrangler widget to show automatic visualization and generate code to fix data quality issues
try:
import sagemaker_datawrangler
except ImportError:
!pip install --upgrade sagemaker-datawrangler
import sagemaker_datawrangler
# Display Pandas DataFrame to view the widget: df, display(df), df.sample()...
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Building wheels for collected packages: sagemaker-scikit-learn-extension
Building wheel for sagemaker-scikit-learn-extension (setup.py) ... done
Created wheel for sagemaker-scikit-learn-extension: filename=sagemaker_scikit_learn_extension-2.5.0-py3-none-any.whl size=71729 sha256=76b9d203698e6687ca7bcb61f9f16e3ce27a8400a4d7aeb243ed88c541c21268
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WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
# Create the train dataset in pandas by reading the csv
# Set the parsing of the datetime column so you can use some of the `dt` features in pandas later
train = pd.read_csv("CSV Files/train.csv",parse_dates=["datetime"])
train.head()
datetime season holiday workingday weather temp atemp \ 0 2011-01-01 00:00:00 1 0 0 1 9.84 14.395 1 2011-01-01 01:00:00 1 0 0 1 9.02 13.635 2 2011-01-01 02:00:00 1 0 0 1 9.02 13.635 3 2011-01-01 03:00:00 1 0 0 1 9.84 14.395 4 2011-01-01 04:00:00 1 0 0 1 9.84 14.395 humidity windspeed casual registered count 0 81 0.0 3 13 16 1 80 0.0 8 32 40 2 80 0.0 5 27 32 3 75 0.0 3 10 13 4 75 0.0 0 1 1
# Simple output of the train dataset to view some of the min/max/varition of the dataset features.
train.describe()
season holiday workingday weather temp \
count 10886.000000 10886.000000 10886.000000 10886.000000 10886.00000
mean 2.506614 0.028569 0.680875 1.418427 20.23086
std 1.116174 0.166599 0.466159 0.633839 7.79159
min 1.000000 0.000000 0.000000 1.000000 0.82000
25% 2.000000 0.000000 0.000000 1.000000 13.94000
50% 3.000000 0.000000 1.000000 1.000000 20.50000
75% 4.000000 0.000000 1.000000 2.000000 26.24000
max 4.000000 1.000000 1.000000 4.000000 41.00000
atemp humidity windspeed casual registered \
count 10886.000000 10886.000000 10886.000000 10886.000000 10886.000000
mean 23.655084 61.886460 12.799395 36.021955 155.552177
std 8.474601 19.245033 8.164537 49.960477 151.039033
min 0.760000 0.000000 0.000000 0.000000 0.000000
25% 16.665000 47.000000 7.001500 4.000000 36.000000
50% 24.240000 62.000000 12.998000 17.000000 118.000000
75% 31.060000 77.000000 16.997900 49.000000 222.000000
max 45.455000 100.000000 56.996900 367.000000 886.000000
count
count 10886.000000
mean 191.574132
std 181.144454
min 1.000000
25% 42.000000
50% 145.000000
75% 284.000000
max 977.000000
# Create the test pandas dataframe in pandas by reading the csv, remember to parse the datetime!
test = pd.read_csv("CSV Files/test.csv",parse_dates=["datetime"])
test.head()
datetime season holiday workingday weather temp atemp \ 0 2011-01-20 00:00:00 1 0 1 1 10.66 11.365 1 2011-01-20 01:00:00 1 0 1 1 10.66 13.635 2 2011-01-20 02:00:00 1 0 1 1 10.66 13.635 3 2011-01-20 03:00:00 1 0 1 1 10.66 12.880 4 2011-01-20 04:00:00 1 0 1 1 10.66 12.880 humidity windspeed 0 56 26.0027 1 56 0.0000 2 56 0.0000 3 56 11.0014 4 56 11.0014
# Same thing as train and test dataset
submission = pd.read_csv("CSV Files/sampleSubmission.csv",parse_dates=["datetime"])
submission.head()
datetime count 0 2011-01-20 00:00:00 0 1 2011-01-20 01:00:00 0 2 2011-01-20 02:00:00 0 3 2011-01-20 03:00:00 0 4 2011-01-20 04:00:00 0
Requirements:
count, so it is the label we are setting.casual and registered columns as they are also not present in the test dataset. root_mean_squared_error as the metric to use for evaluation.best_quality to focus on creating the best model.train_data = train
# Define the label column
label = 'count'
# Define the evaluation metric
eval_metric = 'root_mean_squared_error'
# Set the time limit
time_limit = 600
# Set the preset
preset = 'best_quality'
# Create the predictor
predictor = TabularPredictor(label=label, eval_metric=eval_metric,
learner_kwargs={"ignored_columns": ["casual", "registered"]}).fit(
train_data=train_data,
time_limit=time_limit,
presets=preset
)
No path specified. Models will be saved in: "AutogluonModels/ag-20230528_210642/"
Presets specified: ['best_quality']
Stack configuration (auto_stack=True): num_stack_levels=1, num_bag_folds=8, num_bag_sets=20
Beginning AutoGluon training ... Time limit = 600s
AutoGluon will save models to "AutogluonModels/ag-20230528_210642/"
AutoGluon Version: 0.6.2
Python Version: 3.7.10
Operating System: Linux
Platform Machine: x86_64
Platform Version: #1 SMP Tue Apr 25 15:24:19 UTC 2023
Train Data Rows: 10886
Train Data Columns: 11
Label Column: count
Preprocessing data ...
AutoGluon infers your prediction problem is: 'regression' (because dtype of label-column == int and many unique label-values observed).
Label info (max, min, mean, stddev): (977, 1, 191.57413, 181.14445)
If 'regression' is not the correct problem_type, please manually specify the problem_type parameter during predictor init (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])
Using Feature Generators to preprocess the data ...
Dropping user-specified ignored columns: ['casual', 'registered']
Fitting AutoMLPipelineFeatureGenerator...
Available Memory: 3005.77 MB
Train Data (Original) Memory Usage: 0.78 MB (0.0% of available memory)
Inferring data type of each feature based on column values. Set feature_metadata_in to manually specify special dtypes of the features.
Stage 1 Generators:
Fitting AsTypeFeatureGenerator...
Note: Converting 2 features to boolean dtype as they only contain 2 unique values.
Stage 2 Generators:
Fitting FillNaFeatureGenerator...
Stage 3 Generators:
Fitting IdentityFeatureGenerator...
Fitting DatetimeFeatureGenerator...
Stage 4 Generators:
Fitting DropUniqueFeatureGenerator...
Types of features in original data (raw dtype, special dtypes):
('datetime', []) : 1 | ['datetime']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 5 | ['season', 'holiday', 'workingday', 'weather', 'humidity']
Types of features in processed data (raw dtype, special dtypes):
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 3 | ['season', 'weather', 'humidity']
('int', ['bool']) : 2 | ['holiday', 'workingday']
('int', ['datetime_as_int']) : 5 | ['datetime', 'datetime.year', 'datetime.month', 'datetime.day', 'datetime.dayofweek']
0.3s = Fit runtime
9 features in original data used to generate 13 features in processed data.
Train Data (Processed) Memory Usage: 0.98 MB (0.0% of available memory)
Data preprocessing and feature engineering runtime = 0.33s ...
AutoGluon will gauge predictive performance using evaluation metric: 'root_mean_squared_error'
This metric's sign has been flipped to adhere to being higher_is_better. The metric score can be multiplied by -1 to get the metric value.
To change this, specify the eval_metric parameter of Predictor()
AutoGluon will fit 2 stack levels (L1 to L2) ...
Fitting 11 L1 models ...
Fitting model: KNeighborsUnif_BAG_L1 ... Training model for up to 399.68s of the 599.67s of remaining time.
-101.5462 = Validation score (-root_mean_squared_error)
0.03s = Training runtime
0.1s = Validation runtime
Fitting model: KNeighborsDist_BAG_L1 ... Training model for up to 395.47s of the 595.46s of remaining time.
-84.1251 = Validation score (-root_mean_squared_error)
0.03s = Training runtime
0.1s = Validation runtime
Fitting model: LightGBMXT_BAG_L1 ... Training model for up to 395.11s of the 595.1s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-131.4609 = Validation score (-root_mean_squared_error)
67.85s = Training runtime
7.8s = Validation runtime
Fitting model: LightGBM_BAG_L1 ... Training model for up to 315.87s of the 515.85s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-131.0542 = Validation score (-root_mean_squared_error)
39.05s = Training runtime
1.81s = Validation runtime
Fitting model: RandomForestMSE_BAG_L1 ... Training model for up to 270.12s of the 470.11s of remaining time.
-116.5443 = Validation score (-root_mean_squared_error)
11.9s = Training runtime
0.54s = Validation runtime
Fitting model: CatBoost_BAG_L1 ... Training model for up to 254.83s of the 454.82s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-130.5332 = Validation score (-root_mean_squared_error)
191.55s = Training runtime
0.11s = Validation runtime
Fitting model: ExtraTreesMSE_BAG_L1 ... Training model for up to 59.5s of the 259.49s of remaining time.
-124.5881 = Validation score (-root_mean_squared_error)
4.95s = Training runtime
0.53s = Validation runtime
Fitting model: NeuralNetFastAI_BAG_L1 ... Training model for up to 51.37s of the 251.36s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-138.8018 = Validation score (-root_mean_squared_error)
67.76s = Training runtime
0.42s = Validation runtime
Completed 1/20 k-fold bagging repeats ...
Fitting model: WeightedEnsemble_L2 ... Training model for up to 360.0s of the 178.82s of remaining time.
-84.1251 = Validation score (-root_mean_squared_error)
0.48s = Training runtime
0.0s = Validation runtime
Fitting 9 L2 models ...
Fitting model: LightGBMXT_BAG_L2 ... Training model for up to 178.27s of the 178.25s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-60.2107 = Validation score (-root_mean_squared_error)
53.14s = Training runtime
3.04s = Validation runtime
Fitting model: LightGBM_BAG_L2 ... Training model for up to 119.98s of the 119.96s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-55.1772 = Validation score (-root_mean_squared_error)
25.94s = Training runtime
0.24s = Validation runtime
Fitting model: RandomForestMSE_BAG_L2 ... Training model for up to 89.91s of the 89.9s of remaining time.
-53.4113 = Validation score (-root_mean_squared_error)
26.51s = Training runtime
0.6s = Validation runtime
Fitting model: CatBoost_BAG_L2 ... Training model for up to 60.34s of the 60.32s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-55.573 = Validation score (-root_mean_squared_error)
60.63s = Training runtime
0.06s = Validation runtime
Completed 1/20 k-fold bagging repeats ...
Fitting model: WeightedEnsemble_L3 ... Training model for up to 360.0s of the -4.1s of remaining time.
-53.0998 = Validation score (-root_mean_squared_error)
0.31s = Training runtime
0.0s = Validation runtime
AutoGluon training complete, total runtime = 604.59s ... Best model: "WeightedEnsemble_L3"
TabularPredictor saved. To load, use: predictor = TabularPredictor.load("AutogluonModels/ag-20230528_210642/")
predictor.fit_summary()
*** Summary of fit() ***
Estimated performance of each model:
model score_val pred_time_val fit_time pred_time_val_marginal fit_time_marginal stack_level can_infer fit_order
0 WeightedEnsemble_L3 -53.099799 15.355100 549.653708 0.000796 0.313764 3 True 14
1 RandomForestMSE_BAG_L2 -53.411253 12.014673 409.634342 0.596428 26.507615 2 True 12
2 LightGBM_BAG_L2 -55.177207 11.662676 409.062004 0.244431 25.935277 2 True 11
3 CatBoost_BAG_L2 -55.572998 11.474988 443.760034 0.056743 60.633307 2 True 13
4 LightGBMXT_BAG_L2 -60.210742 14.456702 436.263745 3.038457 53.137018 2 True 10
5 KNeighborsDist_BAG_L1 -84.125061 0.103669 0.029130 0.103669 0.029130 1 True 2
6 WeightedEnsemble_L2 -84.125061 0.104435 0.511747 0.000766 0.482617 2 True 9
7 KNeighborsUnif_BAG_L1 -101.546199 0.103915 0.031923 0.103915 0.031923 1 True 1
8 RandomForestMSE_BAG_L1 -116.544294 0.543514 11.901437 0.543514 11.901437 1 True 5
9 ExtraTreesMSE_BAG_L1 -124.588053 0.528831 4.947814 0.528831 4.947814 1 True 7
10 CatBoost_BAG_L1 -130.533194 0.105419 191.554991 0.105419 191.554991 1 True 6
11 LightGBM_BAG_L1 -131.054162 1.812739 39.047134 1.812739 39.047134 1 True 4
12 LightGBMXT_BAG_L1 -131.460909 7.802163 67.849963 7.802163 67.849963 1 True 3
13 NeuralNetFastAI_BAG_L1 -138.801849 0.417995 67.764336 0.417995 67.764336 1 True 8
Number of models trained: 14
Types of models trained:
{'StackerEnsembleModel_LGB', 'WeightedEnsembleModel', 'StackerEnsembleModel_RF', 'StackerEnsembleModel_CatBoost', 'StackerEnsembleModel_KNN', 'StackerEnsembleModel_NNFastAiTabular', 'StackerEnsembleModel_XT'}
Bagging used: True (with 8 folds)
Multi-layer stack-ensembling used: True (with 3 levels)
Feature Metadata (Processed):
(raw dtype, special dtypes):
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 3 | ['season', 'weather', 'humidity']
('int', ['bool']) : 2 | ['holiday', 'workingday']
('int', ['datetime_as_int']) : 5 | ['datetime', 'datetime.year', 'datetime.month', 'datetime.day', 'datetime.dayofweek']
Plot summary of models saved to file: AutogluonModels/ag-20230528_210642/SummaryOfModels.html
*** End of fit() summary ***
{'model_types': {'KNeighborsUnif_BAG_L1': 'StackerEnsembleModel_KNN',
'KNeighborsDist_BAG_L1': 'StackerEnsembleModel_KNN',
'LightGBMXT_BAG_L1': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1': 'StackerEnsembleModel_LGB',
'RandomForestMSE_BAG_L1': 'StackerEnsembleModel_RF',
'CatBoost_BAG_L1': 'StackerEnsembleModel_CatBoost',
'ExtraTreesMSE_BAG_L1': 'StackerEnsembleModel_XT',
'NeuralNetFastAI_BAG_L1': 'StackerEnsembleModel_NNFastAiTabular',
'WeightedEnsemble_L2': 'WeightedEnsembleModel',
'LightGBMXT_BAG_L2': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2': 'StackerEnsembleModel_LGB',
'RandomForestMSE_BAG_L2': 'StackerEnsembleModel_RF',
'CatBoost_BAG_L2': 'StackerEnsembleModel_CatBoost',
'WeightedEnsemble_L3': 'WeightedEnsembleModel'},
'model_performance': {'KNeighborsUnif_BAG_L1': -101.54619908446061,
'KNeighborsDist_BAG_L1': -84.12506123181602,
'LightGBMXT_BAG_L1': -131.46090891834504,
'LightGBM_BAG_L1': -131.054161598899,
'RandomForestMSE_BAG_L1': -116.54429428704391,
'CatBoost_BAG_L1': -130.5331939673838,
'ExtraTreesMSE_BAG_L1': -124.58805258915959,
'NeuralNetFastAI_BAG_L1': -138.80184878939485,
'WeightedEnsemble_L2': -84.12506123181602,
'LightGBMXT_BAG_L2': -60.21074168177454,
'LightGBM_BAG_L2': -55.17720686751347,
'RandomForestMSE_BAG_L2': -53.41125302253621,
'CatBoost_BAG_L2': -55.5729984932244,
'WeightedEnsemble_L3': -53.0997991005159},
'model_best': 'WeightedEnsemble_L3',
'model_paths': {'KNeighborsUnif_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/KNeighborsUnif_BAG_L1/',
'KNeighborsDist_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/KNeighborsDist_BAG_L1/',
'LightGBMXT_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/LightGBMXT_BAG_L1/',
'LightGBM_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/LightGBM_BAG_L1/',
'RandomForestMSE_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/RandomForestMSE_BAG_L1/',
'CatBoost_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/CatBoost_BAG_L1/',
'ExtraTreesMSE_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/ExtraTreesMSE_BAG_L1/',
'NeuralNetFastAI_BAG_L1': 'AutogluonModels/ag-20230528_210642/models/NeuralNetFastAI_BAG_L1/',
'WeightedEnsemble_L2': 'AutogluonModels/ag-20230528_210642/models/WeightedEnsemble_L2/',
'LightGBMXT_BAG_L2': 'AutogluonModels/ag-20230528_210642/models/LightGBMXT_BAG_L2/',
'LightGBM_BAG_L2': 'AutogluonModels/ag-20230528_210642/models/LightGBM_BAG_L2/',
'RandomForestMSE_BAG_L2': 'AutogluonModels/ag-20230528_210642/models/RandomForestMSE_BAG_L2/',
'CatBoost_BAG_L2': 'AutogluonModels/ag-20230528_210642/models/CatBoost_BAG_L2/',
'WeightedEnsemble_L3': 'AutogluonModels/ag-20230528_210642/models/WeightedEnsemble_L3/'},
'model_fit_times': {'KNeighborsUnif_BAG_L1': 0.03192257881164551,
'KNeighborsDist_BAG_L1': 0.029129505157470703,
'LightGBMXT_BAG_L1': 67.84996318817139,
'LightGBM_BAG_L1': 39.047133684158325,
'RandomForestMSE_BAG_L1': 11.901436805725098,
'CatBoost_BAG_L1': 191.55499148368835,
'ExtraTreesMSE_BAG_L1': 4.9478137493133545,
'NeuralNetFastAI_BAG_L1': 67.76433610916138,
'WeightedEnsemble_L2': 0.4826173782348633,
'LightGBMXT_BAG_L2': 53.13701796531677,
'LightGBM_BAG_L2': 25.935276746749878,
'RandomForestMSE_BAG_L2': 26.507615089416504,
'CatBoost_BAG_L2': 60.63330674171448,
'WeightedEnsemble_L3': 0.3137643337249756},
'model_pred_times': {'KNeighborsUnif_BAG_L1': 0.10391521453857422,
'KNeighborsDist_BAG_L1': 0.1036689281463623,
'LightGBMXT_BAG_L1': 7.802163124084473,
'LightGBM_BAG_L1': 1.812739372253418,
'RandomForestMSE_BAG_L1': 0.5435137748718262,
'CatBoost_BAG_L1': 0.10541868209838867,
'ExtraTreesMSE_BAG_L1': 0.5288305282592773,
'NeuralNetFastAI_BAG_L1': 0.4179952144622803,
'WeightedEnsemble_L2': 0.0007660388946533203,
'LightGBMXT_BAG_L2': 3.038456678390503,
'LightGBM_BAG_L2': 0.2444312572479248,
'RandomForestMSE_BAG_L2': 0.5964279174804688,
'CatBoost_BAG_L2': 0.05674266815185547,
'WeightedEnsemble_L3': 0.0007963180541992188},
'num_bag_folds': 8,
'max_stack_level': 3,
'model_hyperparams': {'KNeighborsUnif_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'KNeighborsDist_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'LightGBMXT_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'RandomForestMSE_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'CatBoost_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'ExtraTreesMSE_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'NeuralNetFastAI_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'WeightedEnsemble_L2': {'use_orig_features': False,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBMXT_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'RandomForestMSE_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'CatBoost_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'WeightedEnsemble_L3': {'use_orig_features': False,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True}},
'leaderboard': model score_val pred_time_val fit_time \
0 WeightedEnsemble_L3 -53.099799 15.355100 549.653708
1 RandomForestMSE_BAG_L2 -53.411253 12.014673 409.634342
2 LightGBM_BAG_L2 -55.177207 11.662676 409.062004
3 CatBoost_BAG_L2 -55.572998 11.474988 443.760034
4 LightGBMXT_BAG_L2 -60.210742 14.456702 436.263745
5 KNeighborsDist_BAG_L1 -84.125061 0.103669 0.029130
6 WeightedEnsemble_L2 -84.125061 0.104435 0.511747
7 KNeighborsUnif_BAG_L1 -101.546199 0.103915 0.031923
8 RandomForestMSE_BAG_L1 -116.544294 0.543514 11.901437
9 ExtraTreesMSE_BAG_L1 -124.588053 0.528831 4.947814
10 CatBoost_BAG_L1 -130.533194 0.105419 191.554991
11 LightGBM_BAG_L1 -131.054162 1.812739 39.047134
12 LightGBMXT_BAG_L1 -131.460909 7.802163 67.849963
13 NeuralNetFastAI_BAG_L1 -138.801849 0.417995 67.764336
pred_time_val_marginal fit_time_marginal stack_level can_infer \
0 0.000796 0.313764 3 True
1 0.596428 26.507615 2 True
2 0.244431 25.935277 2 True
3 0.056743 60.633307 2 True
4 3.038457 53.137018 2 True
5 0.103669 0.029130 1 True
6 0.000766 0.482617 2 True
7 0.103915 0.031923 1 True
8 0.543514 11.901437 1 True
9 0.528831 4.947814 1 True
10 0.105419 191.554991 1 True
11 1.812739 39.047134 1 True
12 7.802163 67.849963 1 True
13 0.417995 67.764336 1 True
fit_order
0 14
1 12
2 11
3 13
4 10
5 2
6 9
7 1
8 5
9 7
10 6
11 4
12 3
13 8 }
predictions = predictor.predict(test)
predictions.head()
0 23.758947 1 41.277710 2 45.014797 3 48.974281 4 51.911652 Name: count, dtype: float32
predictions.describe()
count 6493.000000 mean 101.020172 std 90.073212 min 3.378276 25% 20.027142 50% 64.318069 75% 167.423874 max 363.106232 Name: count, dtype: float64
# Describe the `predictions` series to see if there are any negative values
# How many negative values do we have?
# Set them to zero
predictions[predictions<0] = 0
submission["count"] = predictions
submission.to_csv("submission.csv", index=False)
!kaggle competitions submit -c bike-sharing-demand -f submission.csv -m "first raw submission"
100%|█████████████████████████████████████████| 188k/188k [00:00<00:00, 411kB/s] Successfully submitted to Bike Sharing Demand
My Submissions¶!kaggle competitions submissions -c bike-sharing-demand | tail -n +1 | head -n 6
fileName date description status publicScore privateScore -------------- ------------------- -------------------- -------- ----------- ------------ submission.csv 2023-05-28 21:23:03 first raw submission complete 1.78979 1.78979
1.789¶# Create a histogram of all features to show the distribution of each one relative to the data. This is part of the exploritory data analysis
train.hist(figsize=(20,20))
array([[<AxesSubplot:title={'center':'datetime'}>,
<AxesSubplot:title={'center':'season'}>,
<AxesSubplot:title={'center':'holiday'}>],
[<AxesSubplot:title={'center':'workingday'}>,
<AxesSubplot:title={'center':'weather'}>,
<AxesSubplot:title={'center':'temp'}>],
[<AxesSubplot:title={'center':'atemp'}>,
<AxesSubplot:title={'center':'humidity'}>,
<AxesSubplot:title={'center':'windspeed'}>],
[<AxesSubplot:title={'center':'casual'}>,
<AxesSubplot:title={'center':'registered'}>,
<AxesSubplot:title={'center':'count'}>]], dtype=object)
# Extracting 'hour', 'dayofweek', 'month', and 'year' from 'datetime' and creating new features
train['hour'] = train['datetime'].dt.hour
train['dayofweek'] = train['datetime'].dt.dayofweek
train['month'] = train['datetime'].dt.month
train['year'] = train['datetime'].dt.year
test['hour'] = test['datetime'].dt.hour
test['dayofweek'] = test['datetime'].dt.dayofweek
test['month'] = test['datetime'].dt.month
test['year'] = test['datetime'].dt.year
# Create a histogram of all features
train.hist(figsize=(20,20))
array([[<AxesSubplot:title={'center':'datetime'}>,
<AxesSubplot:title={'center':'season'}>,
<AxesSubplot:title={'center':'holiday'}>,
<AxesSubplot:title={'center':'workingday'}>],
[<AxesSubplot:title={'center':'weather'}>,
<AxesSubplot:title={'center':'temp'}>,
<AxesSubplot:title={'center':'atemp'}>,
<AxesSubplot:title={'center':'humidity'}>],
[<AxesSubplot:title={'center':'windspeed'}>,
<AxesSubplot:title={'center':'casual'}>,
<AxesSubplot:title={'center':'registered'}>,
<AxesSubplot:title={'center':'count'}>],
[<AxesSubplot:title={'center':'hour'}>,
<AxesSubplot:title={'center':'dayofweek'}>,
<AxesSubplot:title={'center':'month'}>,
<AxesSubplot:title={'center':'year'}>]], dtype=object)
# Make 'season' and 'weather' features as categorical
train["season"] = train["season"].astype('category')
train["weather"] = train["weather"].astype('category')
test["season"] = test["season"].astype('category')
test["weather"] = test["weather"].astype('category')
# View are new feature
train.head()
datetime season holiday workingday weather temp atemp \ 0 2011-01-01 00:00:00 1 0 0 1 9.84 14.395 1 2011-01-01 01:00:00 1 0 0 1 9.02 13.635 2 2011-01-01 02:00:00 1 0 0 1 9.02 13.635 3 2011-01-01 03:00:00 1 0 0 1 9.84 14.395 4 2011-01-01 04:00:00 1 0 0 1 9.84 14.395 humidity windspeed casual registered count hour dayofweek month \ 0 81 0.0 3 13 16 0 5 1 1 80 0.0 8 32 40 1 5 1 2 80 0.0 5 27 32 2 5 1 3 75 0.0 3 10 13 3 5 1 4 75 0.0 0 1 1 4 5 1 year 0 2011 1 2011 2 2011 3 2011 4 2011
# View histogram of all features again now with the hour feature
train.hist(figsize=(20,20))
array([[<AxesSubplot:title={'center':'datetime'}>,
<AxesSubplot:title={'center':'holiday'}>,
<AxesSubplot:title={'center':'workingday'}>,
<AxesSubplot:title={'center':'temp'}>],
[<AxesSubplot:title={'center':'atemp'}>,
<AxesSubplot:title={'center':'humidity'}>,
<AxesSubplot:title={'center':'windspeed'}>,
<AxesSubplot:title={'center':'casual'}>],
[<AxesSubplot:title={'center':'registered'}>,
<AxesSubplot:title={'center':'count'}>,
<AxesSubplot:title={'center':'hour'}>,
<AxesSubplot:title={'center':'dayofweek'}>],
[<AxesSubplot:title={'center':'month'}>,
<AxesSubplot:title={'center':'year'}>, <AxesSubplot:>,
<AxesSubplot:>]], dtype=object)
Extracting additional time-related features such as day of the month, week of the year, quarter of the year.
train['dayofmonth'] = train['datetime'].dt.day
train['weekofyear'] = train['datetime'].dt.isocalendar().week
train['quarter'] = train['datetime'].dt.quarter
test['dayofmonth'] = test['datetime'].dt.day
test['weekofyear'] = test['datetime'].dt.isocalendar().week
test['quarter'] = test['datetime'].dt.quarter
train.head()
datetime season holiday workingday weather temp atemp \ 0 2011-01-01 00:00:00 1 0 0 1 9.84 14.395 1 2011-01-01 01:00:00 1 0 0 1 9.02 13.635 2 2011-01-01 02:00:00 1 0 0 1 9.02 13.635 3 2011-01-01 03:00:00 1 0 0 1 9.84 14.395 4 2011-01-01 04:00:00 1 0 0 1 9.84 14.395 humidity windspeed casual registered count hour dayofweek month \ 0 81 0.0 3 13 16 0 5 1 1 80 0.0 8 32 40 1 5 1 2 80 0.0 5 27 32 2 5 1 3 75 0.0 3 10 13 3 5 1 4 75 0.0 0 1 1 4 5 1 year dayofmonth weekofyear quarter 0 2011 1 52 1 1 2011 1 52 1 2 2011 1 52 1 3 2011 1 52 1 4 2011 1 52 1
import seaborn as sns
import matplotlib.pyplot as plt
corr = train.corr()
plt.figure(figsize=(15,10))
sns.heatmap(corr, annot=True, cmap='coolwarm')
plt.show()
From the correlation matrix, we can observe the following key insights:
The "temp" and "atemp" features are highly correlated (0.984948), indicating a strong relationship between actual temperature and perceived temperature.
Bike sharing demand, represented by the "count" feature, shows positive correlations with "temp" (0.394454) and "atemp" (0.389784), suggesting that higher temperatures are associated with increased bike usage.
The "hour" feature has a positive correlation (0.400601) with the bike sharing demand, indicating that certain hours of the day have higher demand for bikes.
The "workingday" feature has a negative correlation (-0.704267) with the "dayofweek" feature, indicating that weekdays are typically associated with working days, while weekends have a higher likelihood of being non-working days or holidays.
The "month" feature exhibits a positive correlation (0.257589) with bike sharing demand, suggesting that bike usage varies across different months.
The "year" feature has a positive correlation (0.260403) with bike sharing demand, indicating that bike usage has increased over the years.
These insights highlight the influence of weather conditions, time of day, and calendar factors on bike sharing demand. They can help in understanding the key drivers of bike usage and inform strategies for optimizing bike sharing systems.
plt.figure(figsize=(15,10))
plt.plot(train['datetime'], train['count'])
plt.title('Time Series of Bike-Sharing Demand')
plt.xlabel('Date')
plt.ylabel('Count')
plt.show()
The Time Series of Bike-Sharing Demand plot showcases the trend of bike-sharing demand over time. Here are the key observations:
Understanding the time series patterns of bike-sharing demand can help in identifying the factors that drive the demand and can aid in making informed decisions related to resource allocation, marketing strategies, and service optimization.
sns.pairplot(train)
plt.show()
The sns.pairplot function provides a visual representation of the relationships between pairs of features in the Bike-Sharing Demand dataset. Here are the key observations from the pairplot:
Overall, the pairplot provides valuable insights into the relationships between features and their impact on bike-sharing demand.
train = train.drop(columns=['casual', 'registered'])
# Define the TabularPredictor object
predictor_new_features = TabularPredictor(
label="count",
problem_type="regression",
eval_metric="root_mean_squared_error"
)
# Fit the model
predictor_new_features.fit(train_data=train, time_limit=600, presets="best_quality")
predictor_new_features.fit_summary()
No path specified. Models will be saved in: "AutogluonModels/ag-20230528_220520/"
Presets specified: ['best_quality']
Stack configuration (auto_stack=True): num_stack_levels=1, num_bag_folds=8, num_bag_sets=20
Beginning AutoGluon training ... Time limit = 600s
AutoGluon will save models to "AutogluonModels/ag-20230528_220520/"
AutoGluon Version: 0.6.2
Python Version: 3.7.10
Operating System: Linux
Platform Machine: x86_64
Platform Version: #1 SMP Tue Apr 25 15:24:19 UTC 2023
Train Data Rows: 10886
Train Data Columns: 16
Label Column: count
Preprocessing data ...
Using Feature Generators to preprocess the data ...
Fitting AutoMLPipelineFeatureGenerator...
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Available Memory: 1549.01 MB
Train Data (Original) Memory Usage: 1.21 MB (0.1% of available memory)
Inferring data type of each feature based on column values. Set feature_metadata_in to manually specify special dtypes of the features.
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Stage 1 Generators:
Fitting AsTypeFeatureGenerator...
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Note: Converting 3 features to boolean dtype as they only contain 2 unique values.
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Stage 2 Generators:
Fitting FillNaFeatureGenerator...
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Stage 3 Generators:
Fitting IdentityFeatureGenerator...
Fitting CategoryFeatureGenerator...
Fitting CategoryMemoryMinimizeFeatureGenerator...
Fitting DatetimeFeatureGenerator...
Stage 4 Generators:
Fitting DropUniqueFeatureGenerator...
Unused Original Features (Count: 1): ['weekofyear']
These features were not used to generate any of the output features. Add a feature generator compatible with these features to utilize them.
Features can also be unused if they carry very little information, such as being categorical but having almost entirely unique values or being duplicates of other features.
These features do not need to be present at inference time.
('UInt32', []) : 1 | ['weekofyear']
Types of features in original data (raw dtype, special dtypes):
('category', []) : 2 | ['season', 'weather']
('datetime', []) : 1 | ['datetime']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 9 | ['holiday', 'workingday', 'humidity', 'hour', 'dayofweek', ...]
Types of features in processed data (raw dtype, special dtypes):
('category', []) : 2 | ['season', 'weather']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 6 | ['humidity', 'hour', 'dayofweek', 'month', 'dayofmonth', ...]
('int', ['bool']) : 3 | ['holiday', 'workingday', 'year']
('int', ['datetime_as_int']) : 5 | ['datetime', 'datetime.year', 'datetime.month', 'datetime.day', 'datetime.dayofweek']
0.3s = Fit runtime
15 features in original data used to generate 19 features in processed data.
Train Data (Processed) Memory Usage: 1.27 MB (0.1% of available memory)
Data preprocessing and feature engineering runtime = 0.35s ...
AutoGluon will gauge predictive performance using evaluation metric: 'root_mean_squared_error'
This metric's sign has been flipped to adhere to being higher_is_better. The metric score can be multiplied by -1 to get the metric value.
To change this, specify the eval_metric parameter of Predictor()
AutoGluon will fit 2 stack levels (L1 to L2) ...
Fitting 11 L1 models ...
Fitting model: KNeighborsUnif_BAG_L1 ... Training model for up to 399.67s of the 599.64s of remaining time.
-101.5462 = Validation score (-root_mean_squared_error)
0.1s = Training runtime
0.2s = Validation runtime
Fitting model: KNeighborsDist_BAG_L1 ... Training model for up to 399.11s of the 599.09s of remaining time.
-84.1251 = Validation score (-root_mean_squared_error)
0.04s = Training runtime
0.1s = Validation runtime
Fitting model: LightGBMXT_BAG_L1 ... Training model for up to 398.74s of the 598.72s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-34.3862 = Validation score (-root_mean_squared_error)
88.7s = Training runtime
8.63s = Validation runtime
Fitting model: LightGBM_BAG_L1 ... Training model for up to 301.54s of the 501.52s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-33.9173 = Validation score (-root_mean_squared_error)
46.57s = Training runtime
3.04s = Validation runtime
Fitting model: RandomForestMSE_BAG_L1 ... Training model for up to 249.43s of the 449.4s of remaining time.
-38.3838 = Validation score (-root_mean_squared_error)
16.12s = Training runtime
0.58s = Validation runtime
Fitting model: CatBoost_BAG_L1 ... Training model for up to 230.35s of the 430.33s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-33.9994 = Validation score (-root_mean_squared_error)
199.02s = Training runtime
0.18s = Validation runtime
Fitting model: ExtraTreesMSE_BAG_L1 ... Training model for up to 27.28s of the 227.25s of remaining time.
-37.8255 = Validation score (-root_mean_squared_error)
7.08s = Training runtime
0.56s = Validation runtime
Fitting model: NeuralNetFastAI_BAG_L1 ... Training model for up to 17.07s of the 217.04s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-112.3675 = Validation score (-root_mean_squared_error)
42.42s = Training runtime
0.47s = Validation runtime
Completed 1/20 k-fold bagging repeats ...
Fitting model: WeightedEnsemble_L2 ... Training model for up to 360.0s of the 170.52s of remaining time.
-32.1571 = Validation score (-root_mean_squared_error)
0.57s = Training runtime
0.0s = Validation runtime
Fitting 9 L2 models ...
Fitting model: LightGBMXT_BAG_L2 ... Training model for up to 169.87s of the 169.85s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-31.2317 = Validation score (-root_mean_squared_error)
31.76s = Training runtime
0.78s = Validation runtime
Fitting model: LightGBM_BAG_L2 ... Training model for up to 133.14s of the 133.11s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-30.6498 = Validation score (-root_mean_squared_error)
26.52s = Training runtime
0.4s = Validation runtime
Fitting model: RandomForestMSE_BAG_L2 ... Training model for up to 102.5s of the 102.48s of remaining time.
-31.5285 = Validation score (-root_mean_squared_error)
34.17s = Training runtime
0.62s = Validation runtime
Fitting model: CatBoost_BAG_L2 ... Training model for up to 65.4s of the 65.37s of remaining time.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
-30.6801 = Validation score (-root_mean_squared_error)
64.96s = Training runtime
0.11s = Validation runtime
Completed 1/20 k-fold bagging repeats ...
Fitting model: WeightedEnsemble_L3 ... Training model for up to 360.0s of the -3.5s of remaining time.
-30.3484 = Validation score (-root_mean_squared_error)
0.32s = Training runtime
0.0s = Validation runtime
AutoGluon training complete, total runtime = 604.01s ... Best model: "WeightedEnsemble_L3"
TabularPredictor saved. To load, use: predictor = TabularPredictor.load("AutogluonModels/ag-20230528_220520/")
*** Summary of fit() ***
Estimated performance of each model:
model score_val pred_time_val fit_time pred_time_val_marginal fit_time_marginal stack_level can_infer fit_order
0 WeightedEnsemble_L3 -30.348431 15.681876 557.767127 0.000849 0.315693 3 True 14
1 LightGBM_BAG_L2 -30.649798 14.173486 426.556313 0.395302 26.515152 2 True 11
2 CatBoost_BAG_L2 -30.680087 13.883778 464.998940 0.105594 64.957778 2 True 13
3 LightGBMXT_BAG_L2 -31.231659 14.556585 431.803588 0.778400 31.762426 2 True 10
4 RandomForestMSE_BAG_L2 -31.528455 14.401731 434.216078 0.623547 34.174917 2 True 12
5 WeightedEnsemble_L2 -32.157071 12.540704 351.006814 0.000880 0.571393 2 True 9
6 LightGBM_BAG_L1 -33.917339 3.042789 46.567111 3.042789 46.567111 1 True 4
7 CatBoost_BAG_L1 -33.999386 0.182528 199.016673 0.182528 199.016673 1 True 6
8 LightGBMXT_BAG_L1 -34.386233 8.626113 88.695049 8.626113 88.695049 1 True 3
9 ExtraTreesMSE_BAG_L1 -37.825541 0.561626 7.083585 0.561626 7.083585 1 True 7
10 RandomForestMSE_BAG_L1 -38.383826 0.584332 16.119021 0.584332 16.119021 1 True 5
11 KNeighborsDist_BAG_L1 -84.125061 0.104061 0.037567 0.104061 0.037567 1 True 2
12 KNeighborsUnif_BAG_L1 -101.546199 0.204905 0.099342 0.204905 0.099342 1 True 1
13 NeuralNetFastAI_BAG_L1 -112.367509 0.471830 42.422813 0.471830 42.422813 1 True 8
Number of models trained: 14
Types of models trained:
{'StackerEnsembleModel_LGB', 'WeightedEnsembleModel', 'StackerEnsembleModel_RF', 'StackerEnsembleModel_CatBoost', 'StackerEnsembleModel_KNN', 'StackerEnsembleModel_NNFastAiTabular', 'StackerEnsembleModel_XT'}
Bagging used: True (with 8 folds)
Multi-layer stack-ensembling used: True (with 3 levels)
Feature Metadata (Processed):
(raw dtype, special dtypes):
('category', []) : 2 | ['season', 'weather']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 6 | ['humidity', 'hour', 'dayofweek', 'month', 'dayofmonth', ...]
('int', ['bool']) : 3 | ['holiday', 'workingday', 'year']
('int', ['datetime_as_int']) : 5 | ['datetime', 'datetime.year', 'datetime.month', 'datetime.day', 'datetime.dayofweek']
Plot summary of models saved to file: AutogluonModels/ag-20230528_220520/SummaryOfModels.html
*** End of fit() summary ***
{'model_types': {'KNeighborsUnif_BAG_L1': 'StackerEnsembleModel_KNN',
'KNeighborsDist_BAG_L1': 'StackerEnsembleModel_KNN',
'LightGBMXT_BAG_L1': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1': 'StackerEnsembleModel_LGB',
'RandomForestMSE_BAG_L1': 'StackerEnsembleModel_RF',
'CatBoost_BAG_L1': 'StackerEnsembleModel_CatBoost',
'ExtraTreesMSE_BAG_L1': 'StackerEnsembleModel_XT',
'NeuralNetFastAI_BAG_L1': 'StackerEnsembleModel_NNFastAiTabular',
'WeightedEnsemble_L2': 'WeightedEnsembleModel',
'LightGBMXT_BAG_L2': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2': 'StackerEnsembleModel_LGB',
'RandomForestMSE_BAG_L2': 'StackerEnsembleModel_RF',
'CatBoost_BAG_L2': 'StackerEnsembleModel_CatBoost',
'WeightedEnsemble_L3': 'WeightedEnsembleModel'},
'model_performance': {'KNeighborsUnif_BAG_L1': -101.54619908446061,
'KNeighborsDist_BAG_L1': -84.12506123181602,
'LightGBMXT_BAG_L1': -34.38623285339942,
'LightGBM_BAG_L1': -33.91733862651761,
'RandomForestMSE_BAG_L1': -38.383825608046195,
'CatBoost_BAG_L1': -33.999386109312795,
'ExtraTreesMSE_BAG_L1': -37.825540568014624,
'NeuralNetFastAI_BAG_L1': -112.3675088612664,
'WeightedEnsemble_L2': -32.15707078392907,
'LightGBMXT_BAG_L2': -31.23165925218751,
'LightGBM_BAG_L2': -30.649798213137323,
'RandomForestMSE_BAG_L2': -31.528454612704277,
'CatBoost_BAG_L2': -30.680086877468266,
'WeightedEnsemble_L3': -30.348430830311507},
'model_best': 'WeightedEnsemble_L3',
'model_paths': {'KNeighborsUnif_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/KNeighborsUnif_BAG_L1/',
'KNeighborsDist_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/KNeighborsDist_BAG_L1/',
'LightGBMXT_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/LightGBMXT_BAG_L1/',
'LightGBM_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/LightGBM_BAG_L1/',
'RandomForestMSE_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/RandomForestMSE_BAG_L1/',
'CatBoost_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/CatBoost_BAG_L1/',
'ExtraTreesMSE_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/ExtraTreesMSE_BAG_L1/',
'NeuralNetFastAI_BAG_L1': 'AutogluonModels/ag-20230528_220520/models/NeuralNetFastAI_BAG_L1/',
'WeightedEnsemble_L2': 'AutogluonModels/ag-20230528_220520/models/WeightedEnsemble_L2/',
'LightGBMXT_BAG_L2': 'AutogluonModels/ag-20230528_220520/models/LightGBMXT_BAG_L2/',
'LightGBM_BAG_L2': 'AutogluonModels/ag-20230528_220520/models/LightGBM_BAG_L2/',
'RandomForestMSE_BAG_L2': 'AutogluonModels/ag-20230528_220520/models/RandomForestMSE_BAG_L2/',
'CatBoost_BAG_L2': 'AutogluonModels/ag-20230528_220520/models/CatBoost_BAG_L2/',
'WeightedEnsemble_L3': 'AutogluonModels/ag-20230528_220520/models/WeightedEnsemble_L3/'},
'model_fit_times': {'KNeighborsUnif_BAG_L1': 0.09934234619140625,
'KNeighborsDist_BAG_L1': 0.0375666618347168,
'LightGBMXT_BAG_L1': 88.69504880905151,
'LightGBM_BAG_L1': 46.5671112537384,
'RandomForestMSE_BAG_L1': 16.11902141571045,
'CatBoost_BAG_L1': 199.01667284965515,
'ExtraTreesMSE_BAG_L1': 7.083585023880005,
'NeuralNetFastAI_BAG_L1': 42.422813177108765,
'WeightedEnsemble_L2': 0.5713932514190674,
'LightGBMXT_BAG_L2': 31.762426137924194,
'LightGBM_BAG_L2': 26.515151739120483,
'RandomForestMSE_BAG_L2': 34.17491674423218,
'CatBoost_BAG_L2': 64.95777821540833,
'WeightedEnsemble_L3': 0.315692663192749},
'model_pred_times': {'KNeighborsUnif_BAG_L1': 0.20490455627441406,
'KNeighborsDist_BAG_L1': 0.10406136512756348,
'LightGBMXT_BAG_L1': 8.626113414764404,
'LightGBM_BAG_L1': 3.0427889823913574,
'RandomForestMSE_BAG_L1': 0.5843319892883301,
'CatBoost_BAG_L1': 0.1825275421142578,
'ExtraTreesMSE_BAG_L1': 0.5616259574890137,
'NeuralNetFastAI_BAG_L1': 0.4718303680419922,
'WeightedEnsemble_L2': 0.0008802413940429688,
'LightGBMXT_BAG_L2': 0.7784004211425781,
'LightGBM_BAG_L2': 0.39530205726623535,
'RandomForestMSE_BAG_L2': 0.623546838760376,
'CatBoost_BAG_L2': 0.10559368133544922,
'WeightedEnsemble_L3': 0.0008492469787597656},
'num_bag_folds': 8,
'max_stack_level': 3,
'model_hyperparams': {'KNeighborsUnif_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'KNeighborsDist_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'LightGBMXT_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'RandomForestMSE_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'CatBoost_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'ExtraTreesMSE_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'NeuralNetFastAI_BAG_L1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'WeightedEnsemble_L2': {'use_orig_features': False,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBMXT_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'RandomForestMSE_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True,
'use_child_oof': True},
'CatBoost_BAG_L2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'WeightedEnsemble_L3': {'use_orig_features': False,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True}},
'leaderboard': model score_val pred_time_val fit_time \
0 WeightedEnsemble_L3 -30.348431 15.681876 557.767127
1 LightGBM_BAG_L2 -30.649798 14.173486 426.556313
2 CatBoost_BAG_L2 -30.680087 13.883778 464.998940
3 LightGBMXT_BAG_L2 -31.231659 14.556585 431.803588
4 RandomForestMSE_BAG_L2 -31.528455 14.401731 434.216078
5 WeightedEnsemble_L2 -32.157071 12.540704 351.006814
6 LightGBM_BAG_L1 -33.917339 3.042789 46.567111
7 CatBoost_BAG_L1 -33.999386 0.182528 199.016673
8 LightGBMXT_BAG_L1 -34.386233 8.626113 88.695049
9 ExtraTreesMSE_BAG_L1 -37.825541 0.561626 7.083585
10 RandomForestMSE_BAG_L1 -38.383826 0.584332 16.119021
11 KNeighborsDist_BAG_L1 -84.125061 0.104061 0.037567
12 KNeighborsUnif_BAG_L1 -101.546199 0.204905 0.099342
13 NeuralNetFastAI_BAG_L1 -112.367509 0.471830 42.422813
pred_time_val_marginal fit_time_marginal stack_level can_infer \
0 0.000849 0.315693 3 True
1 0.395302 26.515152 2 True
2 0.105594 64.957778 2 True
3 0.778400 31.762426 2 True
4 0.623547 34.174917 2 True
5 0.000880 0.571393 2 True
6 3.042789 46.567111 1 True
7 0.182528 199.016673 1 True
8 8.626113 88.695049 1 True
9 0.561626 7.083585 1 True
10 0.584332 16.119021 1 True
11 0.104061 0.037567 1 True
12 0.204905 0.099342 1 True
13 0.471830 42.422813 1 True
fit_order
0 14
1 11
2 13
3 10
4 12
5 9
6 4
7 6
8 3
9 7
10 5
11 2
12 1
13 8 }
predictions_new_features = predictor_new_features.predict(test)
predictions_new_features.head()
0 15.499533 1 11.199882 2 10.766752 3 9.099400 4 8.308702 Name: count, dtype: float32
# Remember to set all negative values to zero
predictions_new_features[predictions_new_features < 0] = 0
# Same submitting predictions
submission_new_features = pd.read_csv("CSV Files/sampleSubmission.csv", parse_dates=["datetime"])
submission_new_features["count"] = predictions_new_features
submission_new_features.to_csv("submission_new_features.csv", index=False)
!kaggle competitions submit -c bike-sharing-demand -f CSV Files/submission_new_features.csv -m "new features"
100%|█████████████████████████████████████████| 188k/188k [00:00<00:00, 488kB/s] Successfully submitted to Bike Sharing Demand
!kaggle competitions submissions -c bike-sharing-demand | tail -n +1 | head -n 6
fileName date description status publicScore privateScore --------------------------- ------------------- -------------------- -------- ----------- ------------ submission_new_features.csv 2023-05-28 22:17:19 new features complete 0.66081 0.66081 submission.csv 2023-05-28 21:23:03 first raw submission complete 1.78979 1.78979
0.66081¶hyperparameter and hyperparameter_tune_kwargs arguments.import autogluon.core as ag
nn_options = { # Specifies non-default hyperparameter values for neural network models
'num_epochs': 10, 'dropout_prob': ag.space.Real(0.0, 0.5, default=0.1), 'layers': ag.space.Categorical([100], [1000], [200, 100], [300, 200, 100]), 'learning_rate': ag.space.Real(1e-4, 1e-2, default=5e-4, log=True), 'activation': ag.space.Categorical('relu', 'softrelu', 'tanh')
}
gbm_options = { #hyperparameter - lightGBM gradient boosted trees
'num_leaves': ag.space.Int(lower=26, upper=66, default=36), 'num_boost_round': 100,
}
hyperparameters = {'GBM': gbm_options, 'NN': nn_options}
num_trials = 10 # Try at most 50 different hyperparameter configurations for each type of model
search_strategy = 'auto'
hyperparameter_tune_kwargs = {
'num_trials': num_trials,
'scheduler' : 'local',
'searcher': search_strategy,
}
predictor_new_hpo = TabularPredictor(label="count", eval_metric="root_mean_squared_error").fit(
train_data=train,
time_limit=600,
presets="best_quality",
hyperparameters=hyperparameters,
hyperparameter_tune_kwargs=hyperparameter_tune_kwargs,
)
No path specified. Models will be saved in: "AutogluonModels/ag-20230528_225927/"
Presets specified: ['best_quality']
Warning: hyperparameter tuning is currently experimental and may cause the process to hang.
Stack configuration (auto_stack=True): num_stack_levels=1, num_bag_folds=8, num_bag_sets=20
Beginning AutoGluon training ... Time limit = 600s
AutoGluon will save models to "AutogluonModels/ag-20230528_225927/"
AutoGluon Version: 0.6.2
Python Version: 3.7.10
Operating System: Linux
Platform Machine: x86_64
Platform Version: #1 SMP Tue Apr 25 15:24:19 UTC 2023
Train Data Rows: 10886
Train Data Columns: 16
Label Column: count
Preprocessing data ...
AutoGluon infers your prediction problem is: 'regression' (because dtype of label-column == int and many unique label-values observed).
Label info (max, min, mean, stddev): (977, 1, 191.57413, 181.14445)
If 'regression' is not the correct problem_type, please manually specify the problem_type parameter during predictor init (You may specify problem_type as one of: ['binary', 'multiclass', 'regression'])
Using Feature Generators to preprocess the data ...
Fitting AutoMLPipelineFeatureGenerator...
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Available Memory: 1488.34 MB
Train Data (Original) Memory Usage: 1.21 MB (0.1% of available memory)
Inferring data type of each feature based on column values. Set feature_metadata_in to manually specify special dtypes of the features.
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Stage 1 Generators:
Fitting AsTypeFeatureGenerator...
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Note: Converting 3 features to boolean dtype as they only contain 2 unique values.
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Stage 2 Generators:
Fitting FillNaFeatureGenerator...
Warning: dtype UInt32 is not recognized as a valid dtype by numpy! AutoGluon may incorrectly handle this feature...
Cannot interpret 'UInt32Dtype()' as a data type
Stage 3 Generators:
Fitting IdentityFeatureGenerator...
Fitting CategoryFeatureGenerator...
Fitting CategoryMemoryMinimizeFeatureGenerator...
Fitting DatetimeFeatureGenerator...
Stage 4 Generators:
Fitting DropUniqueFeatureGenerator...
Unused Original Features (Count: 1): ['weekofyear']
These features were not used to generate any of the output features. Add a feature generator compatible with these features to utilize them.
Features can also be unused if they carry very little information, such as being categorical but having almost entirely unique values or being duplicates of other features.
These features do not need to be present at inference time.
('UInt32', []) : 1 | ['weekofyear']
Types of features in original data (raw dtype, special dtypes):
('category', []) : 2 | ['season', 'weather']
('datetime', []) : 1 | ['datetime']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 9 | ['holiday', 'workingday', 'humidity', 'hour', 'dayofweek', ...]
Types of features in processed data (raw dtype, special dtypes):
('category', []) : 2 | ['season', 'weather']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 6 | ['humidity', 'hour', 'dayofweek', 'month', 'dayofmonth', ...]
('int', ['bool']) : 3 | ['holiday', 'workingday', 'year']
('int', ['datetime_as_int']) : 5 | ['datetime', 'datetime.year', 'datetime.month', 'datetime.day', 'datetime.dayofweek']
0.2s = Fit runtime
15 features in original data used to generate 19 features in processed data.
Train Data (Processed) Memory Usage: 1.27 MB (0.1% of available memory)
Data preprocessing and feature engineering runtime = 0.33s ...
AutoGluon will gauge predictive performance using evaluation metric: 'root_mean_squared_error'
This metric's sign has been flipped to adhere to being higher_is_better. The metric score can be multiplied by -1 to get the metric value.
To change this, specify the eval_metric parameter of Predictor()
AutoGluon will fit 2 stack levels (L1 to L2) ...
WARNING: "NN" model has been deprecated in v0.4.0 and renamed to "NN_MXNET". Starting in v0.6.0, specifying "NN" or "NN_MXNET" will raise an exception. Consider instead specifying "NN_TORCH".
Fitting 2 L1 models ...
Hyperparameter tuning model: LightGBM_BAG_L1 ... Tuning model for up to 179.86s of the 599.67s of remaining time.
0%| | 0/10 [00:00<?, ?it/s] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
10%|█ | 1/10 [00:22<03:23, 22.63s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
20%|██ | 2/10 [00:52<03:34, 26.85s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
30%|███ | 3/10 [01:16<02:58, 25.47s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
40%|████ | 4/10 [01:40<02:29, 24.97s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
50%|█████ | 5/10 [02:03<02:02, 24.42s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
60%|██████ | 6/10 [02:27<01:36, 24.13s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
Stopping HPO to satisfy time limit...
60%|██████ | 6/10 [02:51<01:54, 28.50s/it]
Fitted model: LightGBM_BAG_L1/T1 ...
-40.2554 = Validation score (-root_mean_squared_error)
22.59s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L1/T2 ...
-39.1125 = Validation score (-root_mean_squared_error)
29.77s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L1/T3 ...
-38.4725 = Validation score (-root_mean_squared_error)
23.8s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L1/T4 ...
-121.8294 = Validation score (-root_mean_squared_error)
24.17s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L1/T5 ...
-43.1759 = Validation score (-root_mean_squared_error)
23.43s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L1/T6 ...
-109.5652 = Validation score (-root_mean_squared_error)
23.51s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L1/T7 ...
-38.3638 = Validation score (-root_mean_squared_error)
23.49s = Training runtime
0.0s = Validation runtime
Hyperparameter tuning model: NeuralNetMXNet_BAG_L1 ... Tuning model for up to 179.86s of the 428.5s of remaining time.
0%| | 0/10 [00:00<?, ?it/s] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=24706, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=24706, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
10%|█ | 1/10 [00:05<00:53, 5.99s/it]2023-05-28 23:02:25,000 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=24766, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=24766, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
20%|██ | 2/10 [00:11<00:45, 5.67s/it]2023-05-28 23:02:30,446 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=24829, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=24829, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
30%|███ | 3/10 [00:17<00:39, 5.65s/it]2023-05-28 23:02:36,026 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): ray::_ray_fit() (pid=24832, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=24893, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=24893, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
40%|████ | 4/10 [00:23<00:35, 5.92s/it]2023-05-28 23:02:42,366 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=24992, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=24992, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
50%|█████ | 5/10 [00:28<00:28, 5.79s/it]2023-05-28 23:02:47,948 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=25057, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=25057, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
60%|██████ | 6/10 [00:34<00:22, 5.71s/it]2023-05-28 23:02:53,491 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=25122, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=25122, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
70%|███████ | 7/10 [00:40<00:16, 5.67s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
2023-05-28 23:02:59,671 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
ray::_ray_fit() (pid=25188, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=25188, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
80%|████████ | 8/10 [00:46<00:11, 5.87s/it]2023-05-28 23:03:05,409 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=25282, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=25282, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
90%|█████████ | 9/10 [00:51<00:05, 5.73s/it]2023-05-28 23:03:10,870 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=25346, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=25346, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
100%|██████████| 10/10 [00:58<00:00, 5.80s/it]
No model was trained during hyperparameter tuning NeuralNetMXNet_BAG_L1... Skipping this model.
Completed 1/20 k-fold bagging repeats ...
Fitting model: WeightedEnsemble_L2 ... Training model for up to 360.0s of the 370.32s of remaining time.
2023-05-28 23:03:17,065 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
-37.6393 = Validation score (-root_mean_squared_error)
0.57s = Training runtime
0.0s = Validation runtime
WARNING: "NN" model has been deprecated in v0.4.0 and renamed to "NN_MXNET". Starting in v0.6.0, specifying "NN" or "NN_MXNET" will raise an exception. Consider instead specifying "NN_TORCH".
Fitting 2 L2 models ...
Hyperparameter tuning model: LightGBM_BAG_L2 ... Tuning model for up to 166.34s of the 369.62s of remaining time.
0%| | 0/10 [00:00<?, ?it/s] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
10%|█ | 1/10 [00:22<03:25, 22.85s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
20%|██ | 2/10 [00:46<03:06, 23.27s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
30%|███ | 3/10 [01:10<02:46, 23.85s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
40%|████ | 4/10 [01:34<02:22, 23.80s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
50%|█████ | 5/10 [02:00<02:02, 24.56s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
Stopping HPO to satisfy time limit...
50%|█████ | 5/10 [02:24<02:24, 28.97s/it]
Fitted model: LightGBM_BAG_L2/T1 ...
-36.6163 = Validation score (-root_mean_squared_error)
22.82s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L2/T2 ...
-36.4008 = Validation score (-root_mean_squared_error)
23.53s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L2/T3 ...
-36.6577 = Validation score (-root_mean_squared_error)
24.5s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L2/T4 ...
-102.82 = Validation score (-root_mean_squared_error)
23.7s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L2/T5 ...
-37.1291 = Validation score (-root_mean_squared_error)
25.87s = Training runtime
0.0s = Validation runtime
Fitted model: LightGBM_BAG_L2/T6 ...
-99.7662 = Validation score (-root_mean_squared_error)
24.26s = Training runtime
0.0s = Validation runtime
Hyperparameter tuning model: NeuralNetMXNet_BAG_L2 ... Tuning model for up to 166.34s of the 224.55s of remaining time.
0%| | 0/10 [00:00<?, ?it/s] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=26876, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=26876, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
10%|█ | 1/10 [00:05<00:52, 5.80s/it]2023-05-28 23:05:48,788 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=26939, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=26939, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
20%|██ | 2/10 [00:11<00:45, 5.66s/it]2023-05-28 23:05:54,313 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): ray::_ray_fit() (pid=26936, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27005, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27005, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
30%|███ | 3/10 [00:17<00:40, 5.72s/it]2023-05-28 23:06:00,155 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): ray::_ray_fit() (pid=27002, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27075, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27075, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
40%|████ | 4/10 [00:24<00:38, 6.47s/it]2023-05-28 23:06:07,763 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27139, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27139, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
50%|█████ | 5/10 [00:30<00:30, 6.12s/it] Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
2023-05-28 23:06:13,566 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
ray::_ray_fit() (pid=27205, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27205, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
60%|██████ | 6/10 [00:36<00:24, 6.05s/it]2023-05-28 23:06:19,168 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27302, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27302, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
70%|███████ | 7/10 [00:42<00:18, 6.01s/it]2023-05-28 23:06:25,131 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27393, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27393, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
80%|████████ | 8/10 [00:47<00:11, 5.84s/it]2023-05-28 23:06:30,611 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27459, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27459, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
90%|█████████ | 9/10 [00:53<00:05, 5.82s/it]2023-05-28 23:06:36,348 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting 8 child models (S1F1 - S1F8) | Fitting with ParallelLocalFoldFittingStrategy
ray::_ray_fit() (pid=27524, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 49, in model_trial
time_limit=time_limit,
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/model_trial.py", line 101, in fit_and_save_model
model.fit(**fit_args, time_limit=time_left)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/stacker_ensemble_model.py", line 154, in _fit
return super()._fit(X=X, y=y, time_limit=time_limit, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 251, in _fit
n_repeats=n_repeats, n_repeat_start=n_repeat_start, save_folds=save_bag_folds, groups=groups, **kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/bagged_ensemble_model.py", line 541, in _fit_folds
fold_fitting_strategy.after_all_folds_scheduled()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 536, in after_all_folds_scheduled
raise processed_exception
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 504, in after_all_folds_scheduled
time_end_fit, predict_time, predict_1_time = self.ray.get(finished)
File "/usr/local/lib/python3.7/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/ray/_private/worker.py", line 2280, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(AttributeError): ray::_ray_fit() (pid=27524, ip=169.255.255.2)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/ensemble/fold_fitting_strategy.py", line 375, in _ray_fit
time_limit=time_limit_fold, **resources, **kwargs_fold)
File "/usr/local/lib/python3.7/site-packages/autogluon/core/models/abstract/abstract_model.py", line 703, in fit
out = self._fit(**kwargs)
File "/usr/local/lib/python3.7/site-packages/autogluon/tabular/models/tabular_nn/mxnet/tabular_nn_mxnet.py", line 135, in _fit
try_import_mxnet()
File "/usr/local/lib/python3.7/site-packages/autogluon/core/utils/try_import.py", line 40, in try_import_mxnet
import mxnet as mx
File "/usr/local/lib/python3.7/site-packages/mxnet/__init__.py", line 33, in <module>
from . import contrib
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/__init__.py", line 30, in <module>
from . import text
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/__init__.py", line 23, in <module>
from . import embedding
File "/usr/local/lib/python3.7/site-packages/mxnet/contrib/text/embedding.py", line 37, in <module>
from ... import numpy_extension as _mx_npx
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/__init__.py", line 23, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/numpy_extension/image.py", line 20, in <module>
from ..image import * # pylint: disable=wildcard-import, unused-wildcard-import
File "/usr/local/lib/python3.7/site-packages/mxnet/image/__init__.py", line 22, in <module>
from . import image
File "/usr/local/lib/python3.7/site-packages/mxnet/image/image.py", line 38, in <module>
import cv2
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 181, in <module>
bootstrap()
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 175, in bootstrap
if __load_extra_py_code_for_module("cv2", submodule, DEBUG):
File "/usr/local/lib/python3.7/site-packages/cv2/__init__.py", line 28, in __load_extra_py_code_for_module
py_module = importlib.import_module(module_name)
File "/usr/local/lib/python3.7/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/usr/local/lib/python3.7/site-packages/cv2/gapi/__init__.py", line 301, in <module>
cv.gapi.wip.GStreamerPipeline = cv.gapi_wip_gst_GStreamerPipeline
AttributeError: module 'cv2' has no attribute 'gapi_wip_gst_GStreamerPipeline'
100%|██████████| 10/10 [00:58<00:00, 5.88s/it]
No model was trained during hyperparameter tuning NeuralNetMXNet_BAG_L2... Skipping this model.
Completed 1/20 k-fold bagging repeats ...
2023-05-28 23:06:41,816 ERROR worker.py:400 -- Unhandled error (suppress with 'RAY_IGNORE_UNHANDLED_ERRORS=1'): The worker died unexpectedly while executing this task. Check python-core-worker-*.log files for more information.
Fitting model: WeightedEnsemble_L3 ... Training model for up to 360.0s of the 165.54s of remaining time.
-36.272 = Validation score (-root_mean_squared_error)
0.59s = Training runtime
0.0s = Validation runtime
AutoGluon training complete, total runtime = 435.27s ... Best model: "WeightedEnsemble_L3"
TabularPredictor saved. To load, use: predictor = TabularPredictor.load("AutogluonModels/ag-20230528_225927/")
predictor_new_hpo.fit_summary()
*** Summary of fit() ***
Estimated performance of each model:
model score_val pred_time_val fit_time pred_time_val_marginal fit_time_marginal stack_level can_infer fit_order
0 WeightedEnsemble_L3 -36.271977 0.003667 219.393433 0.001082 0.594797 3 True 15
1 LightGBM_BAG_L2/T2 -36.400794 0.002482 194.296825 0.000094 23.528380 2 True 10
2 LightGBM_BAG_L2/T1 -36.616293 0.002534 193.589968 0.000146 22.821523 2 True 9
3 LightGBM_BAG_L2/T3 -36.657726 0.002491 195.270256 0.000103 24.501811 2 True 11
4 LightGBM_BAG_L2/T5 -37.129110 0.002523 196.635863 0.000135 25.867418 2 True 13
5 WeightedEnsemble_L2 -37.639263 0.001453 47.865143 0.001244 0.568873 2 True 8
6 LightGBM_BAG_L1/T7 -38.363848 0.000104 23.494382 0.000104 23.494382 1 True 7
7 LightGBM_BAG_L1/T3 -38.472461 0.000105 23.801888 0.000105 23.801888 1 True 3
8 LightGBM_BAG_L1/T2 -39.112474 0.000154 29.773199 0.000154 29.773199 1 True 2
9 LightGBM_BAG_L1/T1 -40.255449 0.000103 22.586776 0.000103 22.586776 1 True 1
10 LightGBM_BAG_L1/T5 -43.175926 0.001631 23.425673 0.001631 23.425673 1 True 5
11 LightGBM_BAG_L2/T6 -99.766173 0.002539 195.024213 0.000151 24.255768 2 True 14
12 LightGBM_BAG_L2/T4 -102.819976 0.002516 194.472584 0.000128 23.704139 2 True 12
13 LightGBM_BAG_L1/T6 -109.565161 0.000143 23.514707 0.000143 23.514707 1 True 6
14 LightGBM_BAG_L1/T4 -121.829367 0.000148 24.171821 0.000148 24.171821 1 True 4
Number of models trained: 15
Types of models trained:
{'StackerEnsembleModel_LGB', 'WeightedEnsembleModel'}
Bagging used: True (with 8 folds)
Multi-layer stack-ensembling used: True (with 3 levels)
Feature Metadata (Processed):
(raw dtype, special dtypes):
('category', []) : 2 | ['season', 'weather']
('float', []) : 3 | ['temp', 'atemp', 'windspeed']
('int', []) : 6 | ['humidity', 'hour', 'dayofweek', 'month', 'dayofmonth', ...]
('int', ['bool']) : 3 | ['holiday', 'workingday', 'year']
('int', ['datetime_as_int']) : 5 | ['datetime', 'datetime.year', 'datetime.month', 'datetime.day', 'datetime.dayofweek']
Plot summary of models saved to file: AutogluonModels/ag-20230528_225927/SummaryOfModels.html
*** End of fit() summary ***
{'model_types': {'LightGBM_BAG_L1/T1': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1/T2': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1/T3': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1/T4': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1/T5': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1/T6': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L1/T7': 'StackerEnsembleModel_LGB',
'WeightedEnsemble_L2': 'WeightedEnsembleModel',
'LightGBM_BAG_L2/T1': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2/T2': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2/T3': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2/T4': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2/T5': 'StackerEnsembleModel_LGB',
'LightGBM_BAG_L2/T6': 'StackerEnsembleModel_LGB',
'WeightedEnsemble_L3': 'WeightedEnsembleModel'},
'model_performance': {'LightGBM_BAG_L1/T1': -40.255448619289915,
'LightGBM_BAG_L1/T2': -39.11247429212556,
'LightGBM_BAG_L1/T3': -38.47246129942717,
'LightGBM_BAG_L1/T4': -121.8293672105454,
'LightGBM_BAG_L1/T5': -43.175926470419526,
'LightGBM_BAG_L1/T6': -109.56516071183998,
'LightGBM_BAG_L1/T7': -38.36384847553418,
'WeightedEnsemble_L2': -37.63926260672266,
'LightGBM_BAG_L2/T1': -36.616293007502655,
'LightGBM_BAG_L2/T2': -36.40079359691757,
'LightGBM_BAG_L2/T3': -36.65772569539349,
'LightGBM_BAG_L2/T4': -102.81997585254157,
'LightGBM_BAG_L2/T5': -37.12910954442744,
'LightGBM_BAG_L2/T6': -99.76617250885762,
'WeightedEnsemble_L3': -36.271977458673284},
'model_best': 'WeightedEnsemble_L3',
'model_paths': {'LightGBM_BAG_L1/T1': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T1/',
'LightGBM_BAG_L1/T2': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T2/',
'LightGBM_BAG_L1/T3': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T3/',
'LightGBM_BAG_L1/T4': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T4/',
'LightGBM_BAG_L1/T5': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T5/',
'LightGBM_BAG_L1/T6': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T6/',
'LightGBM_BAG_L1/T7': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L1/T7/',
'WeightedEnsemble_L2': 'AutogluonModels/ag-20230528_225927/models/WeightedEnsemble_L2/',
'LightGBM_BAG_L2/T1': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L2/T1/',
'LightGBM_BAG_L2/T2': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L2/T2/',
'LightGBM_BAG_L2/T3': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L2/T3/',
'LightGBM_BAG_L2/T4': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L2/T4/',
'LightGBM_BAG_L2/T5': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L2/T5/',
'LightGBM_BAG_L2/T6': '/root/cd0385-project-starter/project/AutogluonModels/ag-20230528_225927/models/LightGBM_BAG_L2/T6/',
'WeightedEnsemble_L3': 'AutogluonModels/ag-20230528_225927/models/WeightedEnsemble_L3/'},
'model_fit_times': {'LightGBM_BAG_L1/T1': 22.586775541305542,
'LightGBM_BAG_L1/T2': 29.773199319839478,
'LightGBM_BAG_L1/T3': 23.80188751220703,
'LightGBM_BAG_L1/T4': 24.171821355819702,
'LightGBM_BAG_L1/T5': 23.42567253112793,
'LightGBM_BAG_L1/T6': 23.5147066116333,
'LightGBM_BAG_L1/T7': 23.49438214302063,
'WeightedEnsemble_L2': 0.5688731670379639,
'LightGBM_BAG_L2/T1': 22.8215229511261,
'LightGBM_BAG_L2/T2': 23.528379917144775,
'LightGBM_BAG_L2/T3': 24.501811265945435,
'LightGBM_BAG_L2/T4': 23.70413875579834,
'LightGBM_BAG_L2/T5': 25.867417812347412,
'LightGBM_BAG_L2/T6': 24.255768060684204,
'WeightedEnsemble_L3': 0.594796895980835},
'model_pred_times': {'LightGBM_BAG_L1/T1': 0.00010323524475097656,
'LightGBM_BAG_L1/T2': 0.00015425682067871094,
'LightGBM_BAG_L1/T3': 0.0001049041748046875,
'LightGBM_BAG_L1/T4': 0.0001480579376220703,
'LightGBM_BAG_L1/T5': 0.001630544662475586,
'LightGBM_BAG_L1/T6': 0.00014281272888183594,
'LightGBM_BAG_L1/T7': 0.00010418891906738281,
'WeightedEnsemble_L2': 0.0012438297271728516,
'LightGBM_BAG_L2/T1': 0.00014591217041015625,
'LightGBM_BAG_L2/T2': 9.369850158691406e-05,
'LightGBM_BAG_L2/T3': 0.00010323524475097656,
'LightGBM_BAG_L2/T4': 0.00012826919555664062,
'LightGBM_BAG_L2/T5': 0.0001347064971923828,
'LightGBM_BAG_L2/T6': 0.00015115737915039062,
'WeightedEnsemble_L3': 0.001081705093383789},
'num_bag_folds': 8,
'max_stack_level': 3,
'model_hyperparams': {'LightGBM_BAG_L1/T1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1/T2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1/T3': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1/T4': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1/T5': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1/T6': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L1/T7': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'WeightedEnsemble_L2': {'use_orig_features': False,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2/T1': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2/T2': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2/T3': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2/T4': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2/T5': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'LightGBM_BAG_L2/T6': {'use_orig_features': True,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True},
'WeightedEnsemble_L3': {'use_orig_features': False,
'max_base_models': 25,
'max_base_models_per_type': 5,
'save_bag_folds': True}},
'leaderboard': model score_val pred_time_val fit_time \
0 WeightedEnsemble_L3 -36.271977 0.003667 219.393433
1 LightGBM_BAG_L2/T2 -36.400794 0.002482 194.296825
2 LightGBM_BAG_L2/T1 -36.616293 0.002534 193.589968
3 LightGBM_BAG_L2/T3 -36.657726 0.002491 195.270256
4 LightGBM_BAG_L2/T5 -37.129110 0.002523 196.635863
5 WeightedEnsemble_L2 -37.639263 0.001453 47.865143
6 LightGBM_BAG_L1/T7 -38.363848 0.000104 23.494382
7 LightGBM_BAG_L1/T3 -38.472461 0.000105 23.801888
8 LightGBM_BAG_L1/T2 -39.112474 0.000154 29.773199
9 LightGBM_BAG_L1/T1 -40.255449 0.000103 22.586776
10 LightGBM_BAG_L1/T5 -43.175926 0.001631 23.425673
11 LightGBM_BAG_L2/T6 -99.766173 0.002539 195.024213
12 LightGBM_BAG_L2/T4 -102.819976 0.002516 194.472584
13 LightGBM_BAG_L1/T6 -109.565161 0.000143 23.514707
14 LightGBM_BAG_L1/T4 -121.829367 0.000148 24.171821
pred_time_val_marginal fit_time_marginal stack_level can_infer \
0 0.001082 0.594797 3 True
1 0.000094 23.528380 2 True
2 0.000146 22.821523 2 True
3 0.000103 24.501811 2 True
4 0.000135 25.867418 2 True
5 0.001244 0.568873 2 True
6 0.000104 23.494382 1 True
7 0.000105 23.801888 1 True
8 0.000154 29.773199 1 True
9 0.000103 22.586776 1 True
10 0.001631 23.425673 1 True
11 0.000151 24.255768 2 True
12 0.000128 23.704139 2 True
13 0.000143 23.514707 1 True
14 0.000148 24.171821 1 True
fit_order
0 15
1 10
2 9
3 11
4 13
5 8
6 7
7 3
8 2
9 1
10 5
11 14
12 12
13 6
14 4 }
# Remember to set all negative values to zero
new_predictions_hpo = predictor_new_hpo.predict(test)
new_predictions_hpo[new_predictions_hpo<0] = 0
# Same submitting predictions
submission_new_hpo = pd.read_csv("CSV Files/sampleSubmission.csv", parse_dates=["datetime"])
submission_new_hpo["count"] = new_predictions_hpo
submission_new_hpo.to_csv("submission_new_hpo.csv", index=False)
!kaggle competitions submit -c bike-sharing-demand -f submission_new_hpo.csv -m "new features with hyperparameters"
100%|█████████████████████████████████████████| 188k/188k [00:00<00:00, 465kB/s] Successfully submitted to Bike Sharing Demand
!kaggle competitions submissions -c bike-sharing-demand | tail -n +1 | head -n 6
fileName date description status publicScore privateScore --------------------------- ------------------- --------------------------------- -------- ----------- ------------ submission_new_hpo.csv 2023-05-28 23:08:46 new features with hyperparameters complete 0.47959 0.47959 submission_new_hpo.csv 2023-05-28 22:47:01 new features with hyperparameters complete 0.99321 0.99321 submission_new_features.csv 2023-05-28 22:17:19 new features complete 0.66081 0.66081 submission.csv 2023-05-28 21:23:03 first raw submission complete 1.78979 1.78979
0.47959¶# Taking the top model score from each training run and creating a line plot to show improvement
# You can create these in the notebook and save them to PNG or use some other tool (e.g. google sheets, excel)
fig = pd.DataFrame(
{
"model": ["initial", "add_features", "hpo"],
"score": [-53.099799, -30.348431, -36.271977 ]
}
).plot(x="model", y="score", figsize=(8, 6)).get_figure()
fig.savefig('model_train_score.png')
# Take the 3 kaggle scores and creating a line plot to show improvement
fig = pd.DataFrame(
{
"test_eval": ["initial", "add_features", "hpo"],
"score": [1.78979, 0.66081, 0.47959]
}
).plot(x="test_eval", y="score", figsize=(8, 6)).get_figure()
fig.savefig('model_test_score.png')
# The 3 hyperparameters we tuned with the kaggle score as the result
pd.DataFrame({
"model": ["initial", "add_features", "hpo"],
"timelimit": ["time_limit = 600", "time_limit=600", "time_limit=600"],
"presets": ["presets='best_quality'", "presets='best_quality'", "presets='best_quality'"],
"hp-method": ["none", "problem_type = 'regression'", "nn & GBM"],
"score": [1.78979, 0.66081, 0.47959]
})
model timelimit presets \
0 initial time_limit = 600 presets='best_quality'
1 add_features time_limit=600 presets='best_quality'
2 hpo time_limit=600 presets='best_quality'
hp-method score
0 none 1.78979
1 problem_type = 'regression' 0.66081
2 nn & GBM 0.47959